English

Dienstplanerstellung in Krankenhaeusern mittels genetischer Algorithmen

Neural and Evolutionary Computing 2013-05-31 v1
Authors: Uwe Aickelin
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Abstract

This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems. It shows that such information can significantly enhance performance, but that the choice of information and the way it is included are important factors for success.

Keywords

genetic algorithms hospital scheduling multiple-choice optimisation problem-specific knowledge optimization rostering

Cite

@article{arxiv.1305.7056,
  title  = {Dienstplanerstellung in Krankenhaeusern mittels genetischer Algorithmen},
  author = {Uwe Aickelin},
  journal= {arXiv preprint arXiv:1305.7056},
  year   = {2013}
}

Comments

Diplomarbeit, in German, Universitaet Mannheim, 1996

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